论文最终版

锅炉工技师论文最终版100【精选】锅炉工技师论文火电厂锅炉水冷壁管防腐耐磨研究姓名单摘要:火力发电厂锅炉水冷壁管高温腐蚀和磨损的机理复杂～它与炉膛火焰温度、燃煤的含硫量、烟气与灰分颗粒的冲蚀密切相关。

防止水冷壁高温腐蚀和磨损的常用方法有两类～即非表面防护方法和表面防护方法。

针对太阳纸业热电厂二期四台循环流化床锅炉～现场采用超音速电弧喷涂～涂层层寿命已近四年～认为积极采用超音速电弧喷涂技术是火电厂循环流化床锅炉水冷壁高温防腐耐磨涂层最可靠的解决方法。

关键词:循环流化床锅炉水冷壁高温腐蚀和磨损超音速电弧喷涂一、引言循环流化床锅炉技术是近十几年来迅速发展起来的一项高效、低污染清洁燃烧技术，其主要特点在于燃料及脱硫剂经多次循环，反复地进行低温燃烧和脱硫反应，炉内湍流运动强烈，不但能达到低NOx排放、90%的脱硫效率和与煤粉炉相近的燃烧效率，而且具有燃料适应性广、负荷调节性能好、灰渣易于综合利用等优点，因此国际上这项技术在电站锅炉、工业锅炉和废弃物处理利用等领域得到广泛的商业应用，且向大型循环流化床锅炉方向发展。

目前，循环流化床锅炉存在的严重问题是锅炉金属管壁高温腐蚀和管壁磨损。

循环流化床锅炉金属件磨损因不同厂家出产的锅炉不同，磨损部位、磨损程度等都不相同，主要发生在以下部位: 1、布风装置——风帽的磨损; 2、炉膛下部卫燃带与水冷壁过渡区域的管壁磨损(严重磨损); 3、炉膛角落区域的水冷壁磨损(严重磨损); 4、炉膛一般水冷壁管的磨损(较严重);5、不规则管壁(弯管让管、管壁上的焊缝、炉内测试元件等)的磨损;6、二次风喷嘴的磨损;7、炉内受热面(屏式过热器、水平过热器管屏、埋管)的磨损;8、炉顶受热面的磨损(较严重);9、旋风分离器的磨损(较严重); 10、对流烟道受热面(省煤器两端、空气预热器入口)的磨损。

尤其循环流化床锅炉水冷壁管的管壁高温腐蚀和管壁磨损最为严重，它的直接危害主要表现在以下两个方面:(1)使管壁减薄，一般每年减薄量约为 1mm 左右，严重的可达 5-6mm 年，形成严重的安全运行隐患，增加了电厂的临时性检修和大修工作量，且检修周期大为缩短，给电厂造成很大的经济损失。

中共华南师范大学物理与电信工程学院委员会党校第××期学习班结业论文《科学发展观与大学生理想信念》年级：本科生2009级姓名：张小明学员编号：×××××××××日期：××××年××月××日科学发展观与大学生理想信念张三(华南师范大学物理与电信工程学院，广东广州 510006)摘要：介绍了论文格式和书写，作者可以按此短文的格式排版。

关键词：论文；修改；格式科学发展观既是指导发展的世界观，又是指导发展的方法论。

……它为大学生塑造理想信念提供了科学的方法。

一、科学发展观提升大学生理想信念…………学界有人据此对理想信念的结构作了进一步分层研究，认为在大学生中，理想信念结构至少存在六个典型层[1]，……科学发展观实际上就是共产主义理想信念在当代中国的具体表现形式。

马克思说：“要消灭私有财产的思想，有共产主义思想就完全够了。

而要消灭现实的私有财产，则必须有现实的共产主义行动。

”[2]…………二、理想信念的生成与养成：科学发展观为大学生塑造理想信念提供了科学方法（一）理论学习与实践锻炼相统一…………正如胡锦涛同志指出的那样：“用马克思主义的立场、观念、方法来认识世界，认识人类社会发展的客观规律……把理想信念建立在科学分析的理性基础之上。

”[4]…………（二）理想与现实辩证统一1．科学发展观为大学生塑造理想信念提供了科学方法……科学发展观实际上就是共产主义理想信念在当代中国的具体表现形式。

2．理想信念的生成与养成……所以，当代大学生要自觉做到“知行合一”，真学、真信、真懂、真用马克思主义，只有这样，我们的社会主义事业才能后继有人。

参考文献：[1]王喜荣，张晋昌．理想教育概论[M]．长春：东北师范大学出版社，1987．[2]马克思恩格斯全集，第42卷[M]．北京：人民出版社，1960．[3]马克思恩格斯选集，第1卷[M]．北京：人民出版社，1995．[4]张三.邓小平思想及其现代性. 北京：中国社会科学出版社，2000.……备注：参考文献限于作者亲自阅读、本文明确引用、公开发表或有案可查者。

毕业论文结论范文(精选8篇)论文是一个汉语词语，拼音是lùn wén，古典文学常见论文一词，谓交谈辞章或交流思想。

当代，论文常用来指进行各个学术领域的研究和描述学术研究成果的文章，简称之为论文。

下面是我精心整理的毕业论文结论范文(精选8篇)，仅供参考，大家一起来看看吧。

毕业论文结论篇1经过两个多月的努力，企业职位分析面临的问题及策略论文最终完成在整个设计过程中，出现过很多的难题，但都在教师和同学的帮忙下顺利解决了，在不断的学习过程中我体会到：写论文是一个不断学习的过程，从最初刚写论文时对企业职位面临的问题的模糊认识到最终能够对该问题有深刻的认识，我体会到实践对于学习的重要性，以前只是明白理论，没有经过实践考察，对知识的理解不够明确，经过这次的做，真正做到林论时间相结合。

总之，经过毕业设计，我深刻体会到要做好一个完整的事情，需要有系统的思维方式和方法，对待要解决的问题，要耐心、要善于运用已有的资源来充实自我。

同时我也深刻的认识到，在对待一个新事物时，必须要从整体研究，完成一步之后再作下一步，这样才能更加有效。

毕业论文结论篇2xx年3月，我开始了我的毕业论文工作，时至今日，论文基本完成。

从最初的茫然，到慢慢的进入状态，再到对思路逐渐的清晰，整个写作过程难以用语言来表达。

历经了几个月的奋战，紧张而又充实的毕业设计最终落下了帷幕。

回想这段日子的经历和感受，我感慨万千，在这次毕业设计的过程中，我拥有了无数难忘的回忆和收获。

3月初，在与导师的交流讨论中我的题目定了下来，是：8031单片机控制LED显示屏设计。

当选题报告，开题报告定下来的时候，我当时便立刻着手资料的收集工作中，当时应对浩瀚的书海真是有些茫然，不知如何下手。

我将这一困难告诉了导师，在导师细心的指导下，最终使我对自我此刻的工作方向和方法有了掌握。

在搜集资料的过程中，我认真准备了一个笔记本。

我在学校图书馆，大工图书馆搜集资料，还在网上查找各类相关资料，将这些宝贵的资料全部记在笔记本上，尽量使我的资料完整、精确、数量多，这有利于论文的撰写。

For office use onlyT1________________ T2________________ T3________________ T4________________Team Control Number 46639Problem ChosenCFor office use onlyF1________________F2________________F3________________F4________________2016 MCM/ICM Summary SheetAn Optimal Investment Strategy ModelSummaryWe develop an optimal investment strategy model that appears to hold promise for providing insight into not only how to sort the schools according to investment priority, but also identify optimal investment amount of a specific school. This model considers a large number of parameters thought to be important to investment in the given College Scorecard Data Set.In order to develop the required model, two sub-models are constructed as follows: 1.For Analytic Hierarchy Process (AHP) Model, we identify the prioritizedcandidate list of schools by synthesizing the elements which have an influence on investment. First we define the specific value of any two elements’ effect on investment. And then the weight of each element’s influence on investment can be identified. Ultimately, we take the relevant parameters into the calculated weight, and then we get any school’s recommended value of investment.2.For Return On Investment M odel, it’s constructed on the basis of AHP Model.Let us suppose that all the investment is used to help the students to pay tuition fee.Then we can see optimal investment as that we help more students to the universities of higher return rate. However, because of dropout rate, there will be an optimization investment amount in each university. Therefore, we can change the problem into a nonlinear programming problem. We identify the optimal investment amount by maximizing return-on-investment.Specific attention is given to the stability and error analysis of our model. The influence of the model is discussed when several fundamental parameters vary. We attempt to use our model to prioritize the schools and identify investment amount of the candidate schools, and then an optimal investment strategy is generated. Ultimately, to demonstrate how our model works, we apply it to the given College Scorecard Data Set. For various situations, we propose an optimal solution. And we also analyze the strengths and weaknesses of our model. We believe that we can make our model more precise if more information are provided.Contents1.Introduction 21.1Restatement of the Problem (2)1.2Our Approach (2)2.Assumptions 23.Notations 34.The Optimal Investment Model 44.1Analytic Hierarchy Process Model (4)4.1.1Constructing the Hierarchy (4)4.1.2Constructing the Judgement Matrix (5)4.1.3Hierarchical Ranking (7)4.2Return On Investment Model (8)4.2.1Overview of the investment strategy (8)4.2.2Analysis of net income and investment cost (9)4.2.3Calculate Return On Investment (11)4.2.4Maximize the Total Net Income (11)5.Test the Model125.1Error Analysis (12)5.2Stability Analysis (13)6.Results136.1Results of Analytic Hierarchy Process (13)6.2Results of Return On Investment Model (14)7.Strengths and Weaknesses157.1Strengths (15)7.2Weaknesses (16)References16 Appendix A Letter to the Chief Financial Officer, Mr. Alpha Chiang.171.Introduction1.1Restatement of the ProblemIn order to help improve educational performance of undergraduates attending colleges and universities in the US, the Goodgrant Foundation intends to donate a total of $100,000,000 to an appropriate group of schools per year, for five years, starting July 2016. We are to develop a model to determine an optimal investment strategy that identifies the school, the investment amount per school, the return on that investment, and the time duration that the organization’s money should be provided to have the highest likelihood of producing a strong positive effect on student performance. Considering that they don’t want to duplicate the investments and focus of other large grant organizations, we interpret optimal investment as a strategy that maximizes the ROI on the premise that we help more students attend better colleges. So the problems to be solved are as follows:1.How to prioritize the schools by optimization level.2.How to measure ROI of a school.3.How to measure investment amount of a specific school.1.2Our ApproachWe offer a model of optimal investment which takes a great many factors in the College Scorecard Data Set into account. To begin with, we make a 1 to N optimized and prioritized candidate list of school we are recommending for investment by the AHP model. For the sake that we invest more students to better school, several factors are considered in the AHP model, such as SAT score, ACT score, etc. And then, we set investment amount of each university in the order of the list according to the standard of maximized ROI. The implement details of the model will be described in section 4.2.AssumptionsWe make the following basic assumptions in order to simplify the problem. And each of our assumptions is justified.1.Investment amount is mainly used for tuition and fees. Considering that theincome of an undergraduate is usually much higher than a high school students, we believe that it’s necessary to help more poor students have a chance to go to college.2.Bank rates will not change during the investment period. The variation ofthe bank rates have a little influence on the income we consider. So we make this assumption just to simplify the model.3.The employment rates and dropout rates will not change, and they aredifferent for different schools4.For return on investment, we only consider monetary income, regardlessof the intangible income.3.NotationsWe use a list of symbols for simplification of expression.4.The Optimal Investment ModelIn this section, we first prioritize schools by the AHP model (Section 4.1), and then calculate ROI value of the schools (Section 4.2). Ultimately, we identify investment amount of every candidate schools according to ROI (Section 4.3).4.1Analytic Hierarchy Process ModelIn order to prioritize schools, we must consider each necessary factor in the College Scorecard Data Set. For each factor, we calculate its weight value. And then, we can identify the investment necessity of each school. So, the model can be developed in 3 steps as follows:4.1.1Constructing the HierarchyWe consider 19 elements to measure priority of candidate schools, which can be seen in Fig 1. The hierarchy could be diagrammed as follows:Fig.1AHP for the investment decisionThe goal is red, the criteria are green and the alternatives are blue. All the alternatives are shown below the lowest level of each criterion. Later in the process, each alternatives will be rated with respect to the criterion directly above it.As they build their hierarchy, we should investigate the values or measurements of the different elements that make it up. If there are published fiscal policy, for example, or school policy, they should be gathered as part of the process. This information will be needed later, when the criteria and alternatives are evaluated.Note that the structure of the investment hierarchy might be different for other foundations. It would definitely be different for a foundation who doesn't care how much his score is, knows he will never dropout, and is intensely interested in math, history, and the numerous aspects of study[1].4.1.2Constructing the Judgement MatrixHierarchy reflects the relationship among elements to consider, but elements in the Criteria Layer don’t always weigh equal during aim measure. In deciders’ mind, each element accounts for a particular proportion.To incorporate their judgments about the various elements in the hierarchy, decision makers compare the elements “two by two”. The fundamental scale for pairwise comparison are shown in Fig 2.Fig 2Right now, let's see which items are compared. Our example will begin with the six criteria in the second row of the hierarchy in Fig 1, though we could begin elsewhere if we want. The criteria will be compared as to how important they are to the decisionmakers, with respect to the goal. Each pair of items in this row will be compared.Fig 3 Investment Judgement MatrixIn the next row, there is a group of 19 alternatives under the criterion. In the subgroup, each pair of alternatives will be compared regarding their importance with respect to the criterion. (As always, their importance is judged by the decision makers.) In the subgroup, there is only one pair of alternatives. They are compared as to how important they are with respect to the criterion.Things change a bit when we get to the alternatives row. Here, the factor in each group of alternatives are compared pair-by-pair with respect to the covering criterion of the group, which is the node directly above them in the hierarchy. What we are doing here is evaluating the models under consideration with respect to score, then with respect to Income, then expenditure, dropout rate, debt and graduation rate.The foundation can evaluate alternatives against their covering criteria in any order they choose. In this case, they choose the order of decreasing priority of the covering criteria.Fig 4 Score Judgement MatrixFig 5 Expenditure Judgement MatrixFig 6 Income Judgement MatrixFig 7 Dropout Judgement MatrixFig 8 Debt Judgement MatrixFig 9 Graduation Matrix4.1.3 Hierarchical RankingWhen the pairwise comparisons are as numerous as those in our example, specialized AHP software can help in making them quickly and efficiently. We will assume that the foundation has access to such software, and that it allows the opinions of various foundations to be combined into an overall opinion for the group.The AHP software uses mathematical calculations to convert these judgments to priorities for each of the six criteria. The details of the calculations are beyond the scope of this article, but are readily available elsewhere[2][3][4][5]. The software also calculates a consistency ratio that expresses the internal consistency of the judgments that have been entered. In this case the judgments showed acceptable consistency, and the software used the foundation’s inputs to assign these new priorities to the criteria:Fig 10.AHP hierarchy for the foundation investing decision.In the end, the AHP software arranges and totals the global priorities for each of the alternatives. Their grand total is 1.000, which is identical to the priority of the goal. Each alternative has a global priority corresponding to its "fit" to all the foundation's judgments about all those aspects of factor. Here is a summary of the global priorities of the alternatives:Fig 114.2 ROI Model4.2.1 Overview of the investment strategyConsider a foundation making investment on a set of N geographically dispersed colleges and university in the United States, D = {1, 2, 3……N }. Then we can select top N schools from the candidate list which has been sorted through analytic hierarchy process. The total investment amount is M per year which is donated by the Goodgrant Foundation. The investment amount is j m for each school j D ∈, satisfying the following balance constraint:j j D mM ∈=∑ (1)W e can’t invest too much or too little money to one school because we want to help more students go to college, and the student should have more choices. Then the investment amount for each school must have a lower limit lu and upper limit bu as follows:j lu m bu ≤≤ (2)The tuition and fees is j p , and the time duration is {1,2,3,4}j t ∈. To simplify ourmodel, we assume that our investment amount is only used for freshmen every year. Because a freshmen oriented investment can get more benefits compared with others. For each school j D ∈, the number of the undergraduate students who will be invested is j n , which can be calculated by the following formula ：,jj j j m n j D p t =∈⨯ (3)Figure12The foundation can use the ROI model to identify j m and j t so that it canmaximize the total net income. Figure1 has shown the overview of our investment model. We will then illustrate the principle and solution of this model by a kind of nonlinear programming method.4.2.2 Analysis of net income and investment costIn our return on investment model, we first focus on analysis of net income and investment cost. Obviously, the future earnings of undergraduate students are not only due to the investment itself. There are many meaning factors such as the effort, the money from their parents, the training from their companies. In order to simplify the model, we assume that the investment cost is the most important element and we don’t consider other possible influence factors. Then we can conclude that the total cost of the investment is j m for each school j D ∈.Figure 13For a single student, the meaning of the investment benefits is the expected earnings in the future. Assuming that the student is not going to college or university after graduating from high school and is directly going to work. Then his wage base is 0b as a high school graduate. If he works as a college graduate, then his wage base is 0a . Then we can give the future proceeds of life which is represented symbolically by T and we use r to represent the bank rates which will change over time. We assume that the bank rates will not change during the investment period. Here, we use bank rates in 2016 to represent the r . The future proceeds of life of a single undergraduate student will be different due to individual differences such as age, physical condition environment, etc. If we consider these differences, the calculation process will be complicated. For simplicity’s sake, we uniform the future proceeds of life T for 20 years. Then we will give two economics formulas to calculate the total expected income in the next T years for graduates and high school graduates:40(1)Tk k a u r +==+∑(4) 40(1)T kk b h r +==+∑(5) The total expected income of a graduate is u , and the total expected income of a highschool graduate is h .Then, we continue to analyze the net income. The net income can be calculated by the following formula:os NetIncome TotalIncome C t =- (6) For each school j D ∈, the net income is j P , the total income is j Q , and the cost is j m . Then we will get the following equation through formula (6):j j j P Q m =- (7)Therefore, the key of the problem is how to calculate j Q . In order to calculate j Q, weneed to estimate the number of future employment j ne . The total number of the invested is j n , which has been calculated above. Considering the dropout rates j α and the employment rates j β for each school j , we can calculate the number of future employment j ne through the following formula:(4)(1)jt j j j j n e n βα-=⨯⨯- (8)That way, we can calculate j Q by the following formula:()j j Q ne u h =⨯- (9)Finally, we take Eq. (2) (3) (4) (7) (8) into Eq. (6), and we will obtain Eq. (9) as follows:4(4)00400(1)()(1)(1)j TT t j j j j j k kk k j jm a b P m p t r r βα+-+===⨯⨯-⨯--⨯++∑∑ (10) We next reformulate the above equation of j P for concise presentation:(4)(1)j t j jj j j jc m P m t λα-⨯⨯=⨯-- (11)where jj j p βλ= and 400400(1)(1)TT k kk k a b c r r ++===-++∑∑ .4.2.3 Calculate Return On InvestmentROI is short of return on investment which can be determined by net income andinvestment cost [7]. It conveys the meaning of the financial assessment. For each schoolj D ∈ , the net income is j P , and the investment cost equals to j m . Then the j ROIcan be calculated by the following formula:100%j j jP ROI m =⨯ (12)We substitute Eq. (10) into Eq. (11), and we will get a new formula as follows:(4)((1)1)100%j t j j j jc ROI t λα-⨯=⨯--⨯ (13)4.2.4 Maximize the Total Net IncomeGiven the net income of each school, we formulate the portfolio problem that maximize the total net income, S=Max(4)((1))j t j jj j j j Dj Djc m P m t λα-∈∈⨯⨯=⨯--∑∑ (14)S. T.jj DmM ∈=∑,{1,2,3,4}t = ,j lu m bu ≤≤ ,Considering the constraint jj DmM ∈=∑, we can further simplify the model,S is equivalent to S’=Max(4)((1))j t j jj j j Dj Djc m P t λα-∈∈⨯⨯=⨯-∑∑ (15)S. T.jj DmM ∈=∑,{1,2,3,4t = ,j l u m b u ≤≤. By solving the nonlinear programming problem S’, we can get the sameanswer as problem S.5. Testing the Model 5.1 Error AnalysisSince the advent of analytic hierarchy process, people pay more attention to it due to the specific applicability, convenience, practicability and systematization of the method. Analytic hierarchy process has not reached the ideal situation whether in theory or application level because the results depend largely on the preference and subjective judgment. In this part, we will analyze the human error problem in analytic hierarchy process.Human error is mainly caused by human factors. The human error mainly reflects on the structure of the judgment matrix. The causes of the error are the following points:1. The number of times that human judge the factors’ importance is excessive.2. The calibration method is not perfect.Then we will give some methods to reduce errors:1. Reduce times of human judgment. One person repeatedly gave the samejudgment between two factors. Or many persons gave the same judgment between two factors one time. Finally, we take the average as result.2. Break the original calibration method. If we have defined the ranking vector111121(,...)n a a a a =between the factor 1A with others. Then we can get all theother ranking vector. For example : 12122111(,1...)na a a a a =.5.2 Stability AnalysisIt is necessary to analyze the stability of ranking result [6], because the strong subjectivefactors. If the ranking result changed a little while the judgment changed a lot, we can conclude that the method is effective and the result is acceptable, and vice versa. We assume that the weight of other factors will change if the weight of one factor changed from i ξ to i η:[8](1)(,1,2...,)(1)i j j i i j n i j ηξηξ-⨯==≠- (16)And it is simple to verify the equation:11nii η==∑ (17)And the new ranking vector ω will be:A ωη=⨯ (18)By this method, the Relative importance between other factors remain the same while one of the factor has changed.6. Results6.1 Results of Analytic Hierarchy ProcessWe can ranking colleges through the analytic hierarchy process, and we can get the top N = 20 schools as follows6.2 Results of Return On Investment ModelBased on the results above, we next use ROI model to distribute investment amountj m and time duration j t for each school j D ∈ by solving the following problem:Max (4)((1))j t j jj j j Dj Djc m P t λα-∈∈⨯⨯=⨯-∑∑S. T.jj DmM ∈=∑,{1,2,3,4t = , j l u m b u≤≤ . In order to solve the problem above, we collected the data from different sources. Inthe end, we solve the model with Lingo software. The program code is as follows:model: sets:roi/1..20/:a,b,p,m,t;endsets data:a = 0.9642 0.9250 0.9484 0.9422 0.9402 0.9498 0.90490.9263 0.9769 0.9553 0.9351 0.9123 0.9410 0.98610.9790 0.9640 0.8644 0.9598 0.9659 0.9720;b = 0.8024 0.7339 0.8737 0.8308 0.8681 0.7998 0.74920.6050 0.8342 0.8217 0.8940 0.8873 0.8495 0.87520.8333 0.8604 0.8176 0.8916 0.7527 0.8659;p = 3.3484 3.7971 3.3070 3.3386 3.3371 3.4956 3.22204.0306 2.8544 3.1503 3.2986 3.3087 3.3419 2.78452.9597 2.92713.3742 2.7801 2.5667 2.8058;c = 49.5528;enddatamax=@sum(roi(I):m(I)/t(I)/p(I)*((1-b(I))^4)*c*(1-a(I)+0.05)^(4-t(I)));@for(roi:@gin(t));@for(roi(I):@bnd(1,t(I),4));@for(roi(I):@bnd(0,m(I),100));@sum(roi(I):m(I))=1000;ENDFinally, we can get the investment amount and time duration distribution as follows:7.Strengths and Weaknesses7.1Strengths1.Fixing the bank rates during the investment period may run out, but it will haveonly marginal influences.2.For return on investment, we only consider monetary income, regardless of the3.intangible income. But the quantization of these intangible income is very importantand difficult. It needs to do too much complicated technical analysis and to quantify 4.too many variables. Considering that the investment persists for a short time, thiskind of random error is acceptable.5.Due to our investment which is freshmen oriented, other students may feel unfair.It is likely to produce adverse reaction to our investment strategy.6.The cost estimation is not impeccable. We only consider the investment amount andignore other non-monetary investment.5. AHP needs higher requirements for personnel quality.7.2Weaknesses1.Our investment strategy is distinct and clear, and it is convenient to implement.2.Our model not only identifies the investment amount for each school, but alsoidentifies the time duration that the organization’s money should be provide d.3.Data processing is convenient, because the most data we use is constant, average ormedian.4.Data sources are reliable. Our investment strategy is based on some meaningful anddefendable subset of two data sets.5.AHP is more simple, effective and universal.References[1] Saaty, Thomas L. (2008). Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. Pittsburgh, Pennsylvania: RWS Publications. ISBN 0-9620317-8-X.[2] Bhushan, Navneet, Kanwal Rai (January 2004). Strategic Decision Making: Applying the Analytic Hierarchy Process. London: Springer-Verlag. ISBN 1-8523375-6-7.[3] Saaty, Thomas L. (2001). Fundamentals of Decision Making and Priority Theory. Pittsburgh, Pennsylvania: RWS Publications. ISBN 0-9620317-6-3.[4] Trick, Michael A. (1996-11-23). "Analytic Hierarchy Process". Class Notes. Carnegie Mellon University Tepper School of Business. Retrieved 2008-03-02.[5] Meixner, Oliver; Reiner Haas (2002). Computergestützte Entscheidungs-findung: Expert Choice und AHP – innovative Werkzeuge zur Lösung komplexer Probleme (in German). Frankfurt/Wien: Redline Wirtschaft bei Ueberreuter. ISBN 3-8323-0909-8.[6] Hazelkorn, E. The Impact of League Tables and Ranking System on Higher Education Decision Making [J]. Higher Education Management and Policy, 2007, 19(2), 87-110.[7] Leslie: Trainer Assessment: A Guide to Measuring the Performance of Trainers and Facilitors, Second Edition, Gower Publishing Limited, 2002.[8] Aguaron J, Moreno-Jimenea J M. Local stability intervals in the analytic hierarchy process. European Journal of Operational Research. 2000Letter to the Chief Financial Officer, Mr. Alpha Chiang. February 1th, 2016.I am writing this letter to introduce our optimal investment strategy. Before I describe our model, I want to discuss our proposed concept of a return-on-investment (ROI). And then I will describe the optimal investment model by construct two sub-model, namely AHP model and ROI model. Finally, the major results of the model simulation will be showed up to you.Considering that the Goodgrant Foundation aims to help improve educational performance of undergraduates attending colleges and universities in the US, we interpret return-on-investment as the increased income of undergraduates. Because the income of an undergraduate is generally much higher than a high school graduate, we suggest all the investment be used to pay for the tuition and fees. In that case, if we take both the income of undergraduates’ income and dropout rate into account, we can get the return-in-investment value.Our model begins with the production of an optimized and prioritized candidate list of schools you are recommending for investment. This sorted list of school is constructed through the use of specification that you would be fully qualified to provided, such as the score of school, the income of graduate student, the dropout rate, etc. With this information, a precise investment list of schools will be produced for donation select.Furthermore, we developed the second sub-model, ROI model, which identifies the investment amount of each school per year. If we invest more money in a school, more students will have a chance to go to college. However, there is an optimal investment amount of specific school because of the existence of dropout. So, we can identify every candidate school’s in vestment amount by solve a nonlinear programming problem. Ultimately, the result of the model simulation show that Washington University, New York University and Boston College are three schools that worth investing most. And detailed simulation can be seen in our MCM Contest article.We hope that this model is sufficient in meeting your needs in any further donation and future philanthropic educational investments within the United States.。

新疆外向型农业发展的研究内容摘要：新疆发展外向型农业具有区位条件优越，交通比较发达；资源禀赋较好，特色农产品丰富；已拥有一批具有国际竞争力的出口农产品和相对广阔稳定的国际市场、政策保障措施具体，可操作性强等优势，同时也有政府对外向型农业的发展重视程度不够；资金投入严重不足；缺乏大型龙头企业，精深加工水平低，出口规模小；农产品外贸体制不完善；农产品及加工品存在质量安全隐患等劣势。

加快新疆外向型农业发展步伐应采取如下重点措施：加强农产品出口基地建设；大力发展农业产业化龙头企业；实施品牌战略,打造农产品品牌；积极争取中央政府支持，解决相关问题。

关键词：新疆；外向型农业；发展；目录一、外向型农业概述 (1)（一）外向型农业的概念 (1)（二）外向型农业的特征 (1)二、新疆发展外向型农业的条件 (1)（一）新疆发展外向型农业具有巨大潜力 (1)（二）新疆发展外向型农业的优势 (2)（三）新疆发展外向型农业的劣势 (5)三、新疆外向型农业发展现状及问题 (6)（一）新疆农业发展概况 (6)（二）新疆外向型农业发展现状 (7)（三）新疆发展外向型农业存在的问题 (9)四、推进新疆外向型农业发展的对策措施 (10)（一）加强农产品出口基地建设 (10)（二）大力发展农业产业化龙头企业 (11)（三）实施品牌战略,打造农产品品牌 (12)（四）积极争取中央政府支持，解决相关问题 (13)参考文献 (14)新疆外向型农业发展的研究一、外向型农业概述（一）外向型农业的概念在我国，外向型农业这一概念早在20世纪80年代初期即被提出，但至今尚未获得一致的界定，由于各地区各部门对外向型农业的解释不同，其侧重点也有所不同。

较规范的解释就是一国或地区面向国际市场,借助于国际分工来实现再生产的农业。

其发展的出发点、立足点不是国内市场,而是国际市场,同国际市场进行广泛的生产要素和最终产品的双向交流,借助于国际市场来完成再生产的循环活动；并建立起同国际市场需求变化相适应的生产结构、产品结构、技术结构和组织结构,形成符合国际规范、有利于双向交流的农业运行机制和宏观管理体系。

论文考核小组评语（最终版）第一篇：论文考核小组评语（最终版）导语：我们知道毕业论文答辩是一种有组织、有准备、有计划、有鉴定的比较正规的审查论文的重要形式。

以下是小编为大家整理的论文考核小组评语，欢迎大家阅读与借鉴！论文考核小组评语一在五分钟的陈述中，该生介绍了论文的主要观点、论文的内容与结构，以及论文的写作过程，条理比较清晰，语言无大错，但有时得看讲稿，因此显得准备不足。

对教师提出的第一个问题，该生只是在教师的启发后才做出了基本正确的回答。

对教师提出的第二个问题，该生的回答基本正确，但无形中暴露了将tragic faith写作tragic fate 并非笔误。

对第三个问题，该生的答辩令人满意，但有少量语言错误。

在语音、语调方面，该生存在若干问题。

流利程度不及同一答辩组中的其他同学。

答辩组经过认真讨论，仍然同意通过该生的毕业论文，但要求该生纠正论文中尚存的部分语言错误。

论文考核小组评语二在答辩过程中，该同学介绍了论文的主要观点、内容并回答了答辩委员的提问。

答辩表明:该同学对土地征收补偿制度作了较深入的研究，整理了较多的文献资料，具备了一定的文献综述能力，在土地征收补偿研究方面有新意。

该同学对教师提出的问题，回答基本正确。

另外，论文也有不足指出，如对土地征收所涉及到的深层次的基础理论问题讨论不够深入。

综合指导教师、评阅人的意见和该学生在答辩过程中的表现，答辩小组经过认真讨论，一致同意通过该同学的毕业论文答辩，并建议授予学士学位。

答辩小组意见该生能在规定时间内熟练、扼要地陈述论文的主要内容，回答问题时反映敏捷，思路清晰，表达准确。

答辩小组经过充分讨论，根据该生论文质量和答辩中的表现，同意评定论文为优秀。

答辩组认为,该同学在毕业论文写作过程中，态度端正，论证严谨，论文写作规范，论文写作水平较高，运用理论分析问题和解决问题的能力较强，答辩应对沉着，回答流利准确。

故该同学的毕业论文达到了本专业培养目标要求，建议授予本科学士学位。

太原科技大学本科毕业设计汽车动力性与燃油经济性计算分析学院机械工程学院专业工程机械姓名马勋学号 201018050112班级机自101204评阅老师指导教师张福生完成日期 2014年6月8日太原科技大学Taiyuan University of Science and Technology摘要汽车动力性是指在良好、平直的路面上行驶时，汽车由所受到的纵向外力决定的、所能达到的平均行驶速度。

汽车是一种高效率的运输工具，运输效率之高低在很大程度上取决于汽车的动力性。

所以，动力性是汽车各种性能中最基本、最重要的性能。

动力性代表了汽车行驶可发挥的极限能力。

本文是以桑塔纳2000车型和数据为对象，进行汽车动力性和燃油经济性分析计算，研究了汽车动力性评价的各种方法和评价指标，介绍了动力性评价的主要参数：最高车速、加速时间、最大爬坡度。

首先将汽车发动机以及各原始数据进行汇总并列表，然后通过相关公式计算出用于评价性能的数值（如最高车速，爬坡度等）。

此外，本文还在MATLAB中定义数据变量，构成变量体系，通过编程利用变量绘制曲线,最终确定该车动力性较强，燃油经济性为普通级。

最后根据曲线特性分析该车的动力性和燃油经济性，针对结果提出改进和优化的建议。

关键词：汽车动力性；燃油经济性；MATLAB；优化设计MATLAB vehicle power performance and fuel economy calculation is based on the analysisAbstractVehicle dynamics refers to the good, when driving on a flat road, the car suffered from the decision of the longitudinal force, can achieve an average speed. Automotive is a highly efficient means oftransport, transport efficiency depends largely on the level of dynamic performance of the car. Therefore, power is the most basic variety of performance cars, the most important performance. Dynamic represents the limit of cars with the ability to play.This article is based on data of Santana 2000 models and objects of automotive power and fuel economy calculation analysis, research and evaluation of the various methods of evaluation of vehicle dynamics, and introduces the dynamic evaluation of the main parameters: maximum speed, acceleration time , Max-gradeability. First, gather the data of the car engine and make a list of the raw data, and then calculate the correlation formula which used to evaluate the performance of value (such as maximum speed, climbing, etc.).What’s more, this a rticle defines the data variables, and build the system of data variables, use the variables with programming to paint pics, then sure the vehicle dynamics of Santana 200 is strong, and the economy also.The last step is analysising the vehicle dynamics and economy based on the curves, while providing some advices about the update and Optimization.Key words:Vehicle dynamics;Fuel economy; MATLAB; optimal design目录摘要 IAbstract II引言 1第一章汽车动力性 21.1 汽车动力性指标 21.2 汽车动力性计算 21.2.1 驱动力、各种阻力数学模型的计算 21.2.2 最高车速和最大爬坡角的计算 81.2.3 加速度的计算 81.2.4 动力因数的计算 91.3 汽车驱动力的影响因素 91.3.1 发动机速度特性 91.3.2 传动系统的效率 101.3.3 轮胎的尺寸与形式 10第二章汽车经济性的计算 122.1 循环工况行驶百公里燃油消耗 12第三章汽车数据统计的动力性计算、MATLAB绘图 16 3.1 桑塔纳2000参数 163.2 发动机参数图标 183.2.1 发动机原始数据 183.2.2 汽车运动参数 193.3 汽车功率参数 213.4 爬坡度参数 233.5 MATLAB绘制程序和结果曲线 253.5.1 定义变量 253.5.2 绘制程序和结果曲线 27结论 35参考文献 38附录A 附录A 常用符号表 39致谢 51基于MATLAB的汽车动力性与燃油经济性分析计算引言近年来，随着我国公路的运输的发展，对汽车的动力性要求也越来越高。

昆明理工大学研究生学位论文撰写规范研究生院院字〔2013〕7号学位论文是学位申请人为申请学位而撰写的学术论文，是研究生从事科研工作的成果的主要表现，它集中表明了作者在研究工作中取得的新成果、发明、理论或见解，是评判学位申请人学术水平的重要依据和获得学位的必要条件之一，也是科学研究领域中的重要文献资料和社会的宝贵财富。

为进一步提高我校博士、硕士学位论文的质量，做到学位论文在内容和格式上的规范化、统一化，参照国家标准GB7713-87《科学技术报告、学位论文和学术论文的编写格式》，结合我校具体要求，制定本规范。

1 学位论文基本要求1.1 学位论文的具体要求参照《昆明理工大学学位授予工作细则》(昆理工大校字〔2011〕99号).1.2学位论文一般应用中文撰写，论文内容应立论正确，推理严谨，文字简练，层次分明，说理透彻，数据准确、真实、可靠，结论明确。

字数要求如下:(1) 博士学位论文的正文不少于6万字。

(2) 硕士人文社科门类的学位论文的正文一般在3万字以上，理、工、农、医门类的学位论文的正文一般在4万字以上，数学专业的学位论文字数可参照人文社科门类的规定执行。

1.3 论文作者应在选题前后阅读有关文献，硕士学位申请人的文献阅读量应在40篇以上，其中外文文献不少于三分之一；博士学位申请人的文献阅读量应在70篇以上，其中外文文献不少于三分之一。

综述部分应对所读文献加以分析和综合，在论文中引用了文献内容的，应将其列入参考文献表，并在正文中引用内容处注明参考文献编号（按出现先后顺序编，具体要求见2.2.2.7）。

2 学位论文编写格式2.1学位论文章、条的编写参照国家标准GB1.1-87《标准化工作导则编写标准的基本规定》第8章“标准条文的编排”的有关规定，采用阿拉伯数字分级编导。

示例：第一章第三条的第二条的第五条表示为1.3.2.52.2 论文的构成2.2.1 前置部分2.2.1.1 封面封面是论文的外表面，提供应有的信息，并起保护作用。

Applied Surface Science 258 (2012) 6864–6869Contents lists available at SciVerse ScienceDirectApplied SurfaceSciencej o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /a p s u scPapillaes-enhanced hydrophobicity of large-sizedpolytetrafluoroethylene-polyphenylene sulfite soft film prepared by layer-by-layer constructionCheng Cheng Hou,Wen Jun Wang,Yu Zhang,Zi Sheng Guan ∗College of Materials Science and Engineering,Nanjing University of Technology,Nanjing,210009,Chinaa r t i c l ei n f oArticle history:Received 10January 2012Received in revised form 21March 2012Accepted 21March 2012Available online 4 April 2012Keywords:SuperhydrophobicPolytetrafluoroethylene Polyphenylene sulfite Soft Film Pollen Graina b s t r a c tLarge-sized superhydrophobic soft film with hierarchical structures were prepared by combining papillaes on the polytetrafluoroethylene-polyphenylene sulfite (PTFE-PPS)surface via layer-by-layer construction on the glass substrate and heat treatment processes,therein,the papillaes were formed by 0.1␮m PTFE coated on the pollen grains.The water contact angles (CAs)and sliding angles (SAs)of the films are strongly dependent on the number density of the papillaes on the PTFE-PPS surface.A superhy-drophobic surface with a water CA =151.5◦and SA =4◦was obtained when the number density was about 649mm −2.The papillaes with micro/submicroscale structures play an important role in the formation of the superhydrophobic surface and can change Wenzel-type surface into Cassie–Baxter-type surface.The condensation of water vapor on the Cassie–Baxter-type PTFE-PPS film is much more difficult than that of on the Wenzel-type film.Our method may develop into a facile method to prepare large-sized soft film with low cost,which limited only by the size of the loading substrates.© 2012 Elsevier B.V. All rights reserved.1.IntroductionSuperhydrophobic surfaces that exhibit apparent water con-tact angles greater than 150◦and low water hysteresis,are very important in academic research and potential applications in self-cleaning [1–4],microfluid devices [5,6],liquid transportation [7–11],water collector [12–15]and so on [16–19].A significant number of hydrophobic surfaces have been successfully fabricated [20–29]with a variety of techniques such as sol–gel techniques [30],layer-by-layer deposition [31,32],co-condensation [33],litho-graphic methods [34,35],electrospinning [36],chemical deposition [37],hydrothermal synthesis [38,39]and so on.However,the simple,low-cost,and large-sized fabrication of superhydropho-bic surfaces,which is crucial for practical applications,is rarely achieved.Polytetrafluoroethylene (PTFE)possesses low surface adhesion and low surface energy,high gas permeability,low toxicity,cli-mate hardiness,and excellent chemical stability and high aging resistance [40].Therefore,it is an ideal material to prepare super-hydrophobic surfaces that exhibit many potential applications.Various technologies have been developed to prepare PTFE super-hydrophobic surfaces,including chemical vapor deposition [41,42],vacuum evaporation method [43],plasma [44],ion beam treatment∗Corresponding author.Tel.:+862551875626;fax:+862551875626.E-mail address:zishengguan@ (Z.S.Guan).[45],radio-frequency sputtering and sacrificial colloids [46,47],pulsed laser deposition [48].However,most of these fabricated methods are involved with severe conditions or expensive equip-ments,in addition,the size and shape of the superhydrophobic surfaces were small and flat.Furthermore,PTFE was usually coated on the substrates and difficult to form superhydrophobic soft films.Therefore,it is necessary to develop a new strategy to prepare large-sized superhydrophobic PTFE soft films.Recently,PTFE coat-ings were prepared by PTFE powder,which sprayed on the surface together with other solvent and then sintered under a certain tem-perature [49],however,it hardly adhere to the substrate due to its low surface energy.In addition,polyphenylene sulfite (PPS)polymer possesses high temperature resistance,good mechanical properties,exceptional chemical,solvent resistance,high dimensional stability and out-standing adhesive properties [50–52],and thus it is an ideal cohesive material to improve the strength and flexibility of the PTFE film.Jung et al.reported that microstructures can generally pro-vide a higher roughness and nanostructures can keep air pocket,which keep water penetrate into the valleys and obtain a low slid-ing angle [53].To achieve a stable PTFE-coated superhydrophobic surface,the key factor is to construct a high roughness surface with micro/nanostructures due to PTFE possesses very low sur-face energy.Nosonovsky theoretically analyzed the stability of a superhydrophobic surface and pointed out that the most promis-ing is to possess a biomimetic hierarchical structures for a stable0169-4332/$–see front matter © 2012 Elsevier B.V. All rights reserved./10.1016/j.apsusc.2012.03.120C.C.Hou et al./Applied Surface Science258 (2012) 6864–68696865Scheme1.Fabrication of superhydrophobic PTFE-PPS softfilm combined with PTFE-coated pollen grains.superhydrophobic surface,on which nanoroughness is added to microroughness[54].Therefore,if the PTFE surfaces possess micropatterns that combined with nanopatterns,we could obtain the superhydrophobic PTFEfilm.As we known,microscale pollen grains are ubiquitous,inexpensive and environmentally benign natural product with high degree of species-specific morpholog-ical complexity with nanounits combined on microstructures that have been used as templates to fabricate oxides with distinguish surface structures[55].In this paper,we took advantages of the microstructures of the pollen to increase the surface roughness and hierarchical structures,and prepared superhydrophobic PTFE-PPS composite softfilm by combining lotus-leaf-like papillaes onto PTFE-PPS surface and its properties were investigated.2.Experimental2.1.Materials0.1␮m and4␮m PTFE powders which corresponding melting point is328–331◦C were used in our experiments.No decompo-sition products of the two-type PTFE powders produced below 425◦C.The0.1␮m PTFE powders were purchased from Reliber, USA.The4␮m PTFE powders were purchased from Experimental Micropowder Factory of Nanjing.Rape pollen grains were pur-chased from Nanjing market,which were washed with alcohol in an ultrasonic cleaner for0.5h for2times to completely clean some impurity on the exine,and then dried in an oven at90◦C.After completely dried,the pollen grains were dispersed with a200-mesh sifter.PPS powers were purchased from Zhejiang Shengda Chemical Co.,Ltd.2.2.Treatment of glass substratesGlass substrates(3.5cm×2.5cm)were immersed in a piranha mixture solution(the volume ratio of98%H2SO4–30%H2O2is 3:1)and slightly boiling treated for30min,and then rinsed with plenty of water.The hydrophilized glass substrates were put into deionized water in a sealed container and used in our experiments without any further treatment.2.3.Preparation of superhydrophobic PTFE coating on glass substratesThe procedure for the preparation of the superhydrophobic sur-face is schematically shown in Scheme1.Wefirstly prepared a PPS layer on the substrate and then annealed at about340◦C to form PPSfilm.After that,a4␮m-PTFE layer was loaded on the PPSfilm. Following,0.1␮m PTFE-coated pollen grains were cast onto the annealed PTFE/PPS coating.The superhydrophobic PTFE-PPSfilm can be obtained after heat treatment at about340◦C.The details are described as follows:2.3.1.Fabrication of PPS coatingA hydrophilized glass substrate was immersed in deionized water.PPS powders were dispersed on the water surface through a200-mesh sifter and then were sonicated for a few minutes to disperse them well on the water surface.When a compact PPS par-ticles layer formed,the deionized water was carefully extracted by a syringe,at last the compact PPS particles layer was transferred on the glass substrate.The unwanted PPS particles on the substrate were slowly blown away from the surface.After that,the sam-ple was annealed at340◦C for1h to make the PPS particles melt together and adhere to the substrate.2.3.2.Preparation of4 m PTFE/PPS-based coating4␮m PTFE powders were dispersed on the PPS-based glass sub-strate using the same method as above.After that,the as-prepared sample was annealed at340◦C for1h to make the PTFE particles melt together and adhere to the PPS-based glass substrate to forma water-repellent PTFE/PPS-based coating.2.3.3.Preparation of0.1 m PTFE-coated pollen grainsThe cleaned pollen grains were mixed with0.1␮m-PTFE pow-ders in a ceramic mortar,and some alcohol was added into the mixture to make the PTFE particles adhere well on the pollen exine with rubbing.After mixed for0.5h,the preliminary0.1␮m PTFE-coated pollen grains were prepared.We compared series of mass ratio of pollen to PTFE to preparation of hydrophobic surfaces.The results indicate that if the mass ratio is too low,the pollen grains cannot be capsulated completely by PTFE.While the mass ratio is very high,it will exist many residual PTFE particles.Therefore,the mass ratio,m pollen:m PTFE=1:2,was selected in our experiments. 2.3.4.Fabrication of superhydrophobic PTFE-PPS coatingcombined with PTFE-coated pollen grainsThe as-prepared0.1␮m PTFE-coated pollen grains were equably cast onto above-annealed PTFE/PPS coating through a200-mesh sifter and then were heat-treated at340◦C for1h to make the PTFE particles on the pollen grains melt together and further adhere to the pollen exine and the PTFE-PPS-based coating.The number den-sity of the pollen grains on the surface was controlled by the sifting time.6866 C.C.Hou et al./Applied Surface Science 258 (2012) 6864–6869Fig.1.SEM images of (a)4␮m-PTFE/PPS coating formed by heat treatment of 4␮m-PTFE particles layer on a glass substrate at 340◦C for 1h,and (b)the detailed structures of (a).The insets are the digital photographs of water droplets on the coating in the horizontal and vertical situation,respectively.PTFE-PPS soft film can be obtained by soaking the as-prepared sample into water,due to the hydrophilicity of the glass substrate,water penetrated into the coating along the side of glass and then peeled the coating off the glass substrate by the buoyancy of water.2.4.CharacterizationScanning electron microscopy (SEM)images were obtained from Hitachi S-3000scanning electron microscope.The static con-tact angles (CAs)and sliding angles (SAs)of the as-prepared surfaces on the glass substrate were measured on Krüss DSA 100(Germany)under ambient conditions using a 5␮L water droplet as the indicator.Data were averaged over 5-times measurements at different places on the sample.3.Results and discussionOur method to prepare hydrophobic PTFE-PPS-based coating is simple.The 4␮m PTFE powders were dispersed on water surface and formed a compact layer under the cooperation of the water-repellent PTFE particles and water surface tension,and were easily transferred onto PPS-based glass substrate (as shown in Scheme 1).The wrinkle-textured PTFE coating with valleys and 1–5␮m pores was formed after the as-prepared layer was heat treated at 340◦C for 1h and then cooled to room temperature (as shown in Fig.1),which shows a water CA =131.2◦(see the inset in Fig.1a),higher than that of the flat PTFE film (108◦)due to the roughness was increased on the surface [56,57].Furthermore,the coating pins a 5␮L water drop,which cannot roll off the PTFE surface even the substrate tilt to 90◦(see the inset in Fig.1b).The spherical rape pollen grains have about 25␮m diameter and 0.4–1␮m pores on the surface and the width of the wall between pores is about 0.6␮m (see Fig.2a).0.1␮m-PTFE parti-cles were preliminarily melted on the surface of the pollen grains and then randomly distributed on the wrinkle-textured PTFE-PPS-based coating to formation of many “islands”on the surface after heat-treated at 340◦C for 1h (see Fig.2b).The leaf-lotus-like surface was obtained (see Fig.2c),which exhibits papillary microstructures with the diameter of about 40␮m.Fig.2d shows the magnified image of a typical single papillae.The detailed structures indicate that the wrinkled struc-tures with many valleys on the papillae are at the range of micro/nanoscales,the corresponding rims are 0.1–0.5␮m width and 0.5–2␮m length.These results show the PTFE particles melted together and adhered to the pollen exine and the PTFE/PPS-based coating.The resulting is the mechanical strength,stability and dura-bility of the coating could be enhanced.This lotus-leaf-like surface shows the super-hydrophobic characteristics with a contact angle of about 153.8±1.7◦(see Fig.2b),and a low sliding angle of about 4◦.Compared to Fig.1,the hydrophobicity is obviously enhanced by the papillaes.The wettability of the as-prepared surfaces was studied in detail by measurement of water CAs and SAs,respectively.The results indicate that the water CAs and SAs vary significantly depending upon the number density of the papillaes on the surface,i.e.,the water CAs increased whereas the SAs decreased with increasing the number density of the papillaes (see Fig.3).When the num-ber attained 649mm −2,the water CAs obtained a value of about 151.5±1.7◦and the SAs reach a value of about 4◦.The low SA value,which indicates the difference between the advancing and reducing angles,demonstrates the hysteresis is small.The higher water CA and the lower SA of the as-prepared PTFE-PPS surface combined with papillaes indicate that the water droplets do not penetrate into the valleys,but rather suspend on the surface.Therefore,the papillaes formed by PTFE coated on the pollen grains distributed on the surface play an important role in formation of the super-hydrophobicity.Pollen grains with the size of decades of micrometers are homo-geneous and play as carriers,i.e.,the tiny PTFE particles covered on the microscale pollen grains surface,on which are of benefit to form wrinkle-textured papillaes after heat treated at 340◦C (see Fig.2c and d).These papillaes were combined on the PTFE-PPS-based coat-ing and formed convex microstructures,which could provide a higher roughness factor and increased water contact angle,and the submicrometer wrinkles existed on the surface of the bumps,which are well benefit to form air pocket formation and thus decreased the water sliding angles.Theoretically,a thorough understanding of the hydrophobicity of the as-prepared PTFE/PPS films and the superhydrophobicity of the papillaes-enhanced PTFE-PPS film can be obtained from the Wenzel and Cassie–Baxter equation,respectively.The PTFE surface with microscale wrinkle-textured structures (see Fig.1a and b)shows a higher water CA than that of the smooth PTFE surface (Â0∼108◦),and this can be explained by the Wenzel equation,cos Âw =r cos Â0(1)where Âw and Â0represent the water CA on the rough and smooth surfaces,respectively;r is the roughness factor.For the wrinkle-textured PTFE surface with a water CA =131.2◦,r is calculated to be 2.13.However,water droplet is easy to penetrate into theC.C.Hou et al./Applied Surface Science 258 (2012) 6864–68696867Fig.2.(a)SEM images of pollen grains,(b)0.1␮m-PTFE-coated pollen grains combined on the PTFE-PPS-based coating,SEM images of (c)and (d)the detailed structures of a 0.1␮m-PTFE-coated pollen grain and static contact angle.The insets in (a)and (b)are the detail structures of the pollen grain and the water contact angle,respectively.microscale valleys and pores due to its concave and lack of hierar-chical structures.Therefore,the contact area between the water and the PTFE surface is large (see Fig.4a)and the resulting is the water droplet was pinned on the surface (see the inset in Fig.1b).However,when the papillaes were distributed on the film to form a lotus-leaf-like surface with convex structures,theFig.3.Relationship of water CAs and SAs with the number density of the papillaes on the PTFE/PPS surface.The number density of the papillaes was rudely counted on these microphotographs,and a round box with the same shape of the PTFE-coated pollen grain was used to count the number.The counted area is ∼1mm 2.hydrophobicity increased significantly.The micro/submicroscale hierarchical structures,which possess a higher roughness than that of the surface constructed only by one-length-scale structure (i.e.microstructure or nanostructure),decreases the contactareaFig.4.Wetting properties of the 4␮m PTFE/PPS coating according to the Wenzel model (a),and PTFE/PPS-based coating combined with PTFE-coated pollen grains according to the Cassie–Baxter model (b).6868 C.C.Hou et al./Applied Surface Science 258 (2012) 6864–6869Fig.5.(a)Photograph of the papillaes-enhanced PTFE-PPS soft film,the right part was rolled up the bottom surface,it is smooth.(b)Scheme of water vapor condensa-tion of the soft film,which was stick on the slope Al sheet.Water vapor was generated by bubbling N 2gas at 80◦C.(c)and (d)Photographs of the water condensed on the 4␮m PTFE-PPS and the papillaes-enhanced PTFE-PPS soft film,respectively.between solid and liquid at the interface contributes a higher static water CA,as the scheme shown in Fig.4b.Therefore,it is valid for describing with the Cassie–Baxter equationcos Âc =f 1cos Â0−f 2(2)where Âc and Â0represent the Cassie water CA on the rough and smooth surfaces,respectively;f 1and f 2are the fraction areas of the solid and air on the surface,respectively (here,f 1+f 2=1).For the superhydrophobic PTFE coating with a water CA =151.5◦,the cor-responding f 1and f 2are 0.175and 0.825,respectively.The large fraction area of air on the surface greatly increased the air/water interface,effectively prevented the penetration of water droplets into the valleys,and therefore decreased the adhesion of a water droplet to the solid surface and contact angle hysteresis.Moreover,the hierarchical structures on the papillaes are capable of decreas-ing the continuity of the three-phase contact line at the solid-liquid interface (see Fig.4b).According to McCarthy,the discontinuity of the three-phase contact lines will lead to less contact angle hys-teresis,and low water SA [58].McHale et al.theoretically analyzed through Wenzel’s and Cassie–Baxter equation and pointed out that both Wenzel’s and Cassie–Baxter water CA increased with the increasing of the rough-ness,however,the hysteresis will be increased on a Wenzel-type surface and decreased on a Cassie–Baxter-type surface [59].How-ever,the thermodynamic transition between Cassie and Wenzel states is decided by the solid–liquid interface fraction f 1.If f 1lies in the range of 0.0873–0.1939,corresponding to a solid-liquid interface fraction between 8.7%and 19.4%,it belongs to a Cassie-type surface [54].In our experiments,it is a good strategy of using the number density of papillaes to vary the roughness and the water hysteresis of the surface.Papillaes distributed on the PTFE-PPS-based film to form convex struc-tures,even if the convex structures are sparse,the water SA also drastically decreased,for example,the number density of papillaes is about 264mm −2,the water SA decreased to ∼32◦.When the papillaes is 649mm −2,a Cassie–Baxter-type superhy-drophobic surface with water CA =151.5◦and the SA =4◦was obtained (see Fig.2).We soaked the as-prepared PTFE-PPS composite coating into the water.After about 3h,the coating peeled off from the glass sub-strate and obtained the soft film with the size of 29cm ×15cm,as the photograph shown in Fig.5a.The results of water vapor condensation indicate that water vapor immediately condensed on the 4-␮m PTFE-PPS film,but can be hardly condensed on the papillaes-enhanced PTFE-PPS soft film,as shown in Fig.5c and 5d,respectively.After 3min,the water drops condensed on the 4␮m PTFE-PPS film were observed,while only mist formed on the papillaes-enhanced PTFE-PPS soft film.Furthermore,the water volatilized quickly on the papillaes-enhanced PTFE-PPS soft film compared to that on the 4␮m PTFE-PPS coating.Theses results indicate that water vapor is easy to condensation on the Wenzel-type surface and difficult to condensation on the Cassie-type surface.4.ConclusionsThe superhydrophobic soft film with hierarchical structures can be prepared by combining PTFE-coated pollen grains on the PTFE-PPS surface via layer-by-layer construction on the glass sub-strate.The PTFE-coated pollen grains with papillae structure play an important role in the formation of the superhydrophobic sur-face and can change Wenzel-type surface into Cassie–Baxter-type surface.Our method may be a good strategy to prepare large-sized PTFE-PPS soft film with low cost using the commercial Teflon.C.C.Hou et al./Applied Surface Science258 (2012) 6864–68696869AcknowledgmentProject supported by the National Natural Science Foundation of China(no.20573055,21071081)and the Natural Science Foun-dation for Universities of Jiangsu province(no.04KJB430039). 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